Automated Quality Control and Traceability

Overview integrates image capture and AI into every step of the manufacturing process, helping your team accelerate product development, reduce rework, and improve yields.

Seamless quality control and traceability

Always have a traceable visual record of every unit built. Quickly review visual records of failed items, inspection results, and other issues with all of your data stored in a single repository.

Our intelligent AI can help you quickly identify the root cause of production problems and quality issues. Whether you are remote or on-site, always have access to the beat of your production line.

Make better real-time decisions
from anywhere

Easily search and analyze every part and product throughout the manufacturing process, from the moment when materials enter the factory to when final products are shipped.

Information is automatically captured via computer vision algorithms and combined with internal data, allowing you to quickly analyze inspection results, assembly details, and time spent at each station. Enabling your team to more effectively reduce recalls, quarantine times, and customer complaints.

Automate your inspection, no machine
learning expertise required

Our deep learning computer vision algorithms are designed specifically for manufacturing. Our algorithms learn your product over time and allow you to automate your inspection leading to improved yields and faster product ramp-ups.

Whether it is an anomaly on a complex part, verifying text, or pattern changes – our software can help you identify it and remove the need for costly manual inspection.

Easily integrates into
your workflow

Simply capture images with an Overview camera, your mobile  device, or an existing camera system

Remotely access the Overview dashboard via your tablet, computer, or mobile device

Easily integrate with your MES, PLC and other internal systems

Open API Access

Improve your factory performance

Whether its your first prototype or you are building at scale, Overview can help you build faster, improve your yields and reduce costs associated with scrap, rework, and returns.

Russell Nibbelink

Co-founder & Head of Engineering
Russell is a co-founder and head of engineering of Overview. At Overview, Russell helps customers implement cutting edge high speed Deep Learning algorithms. Prior to joining Overview, he was a software engineer at Salesforce where he worked on web-scale infrastructure projects. Russell received his BS from UC Berkeley’s College of Engineering, where he helped teach a class on High Performance Computing.

Chris Van Dyke

Co-founder & CEO

Chris Van Dyke is a co-founder and the CEO of Overview. Prior to founding Overview, Chris spent eight years in manufacturing engineering at Tesla. Most recently, he led the 80 person battery design team through the launch of the Model 3. During which time he was principally responsible for taking the team from battery design to high-volume production. Earlier in his career at Tesla he managed the infrastructure and equipment design for the first Gigafactory project including equipment for supporting battery cell manufacturing. Chris also launched Tesla’s Electric Vehicle Supercharger Program, which currently has more than 16,000 stations nationwide.

Chris holds several patents of XYZ, and led custom equipment design for a major XYZ type of company while a Senior Engineer at H2Gen Innovations. Chris received his BS from Stanford University in Mechanical Engineering and an MS from the University of Virginia in Chemical Engineering.

Austin Appel

Co-founder & Head of Product

Austin Appel is a co-founder and head of product of Overview. At Overview, Austin leads product development and operations. Prior to Overview, Austin spent four years at Tesla in roles across battery manufacturing and R&D. He led the DFM and automation efforts for Model 3 battery pack production at Tesla’s first Gigafactory. Previously he expanded Tesla’s production of Model S and X battery packs through equipment design and implementation. He holds a dual bachelors degree in Manufacturing Engineering and Mechanical Engineering from Northwestern University.